Wray C M, Bishop S R
Department of Mathematics, University College London Gower Street, London WCIE 6BT, UK.
Sci Rep. 2014 Sep 12;4:6355. doi: 10.1038/srep06355.
While much recent research has focused on understanding isolated cascades of networks, less attention has been given to dynamical processes on networks exhibiting repeated cascades of opposing influence. An example of this is the dynamic behaviour of financial markets where cascades of buying and selling can occur, even over short timescales. To model these phenomena, a stochastic pulse-coupled oscillator network with upper and lower thresholds is described and analysed. Numerical confirmation of asynchronous and synchronous regimes of the system is presented, along with analytical identification of the fixed point state vector of the asynchronous mean field system. A lower bound for the finite system mean field critical value of network coupling probability is found that separates the asynchronous and synchronous regimes. For the low-dimensional mean field system, a closed-form equation is found for cascade size, in terms of the network coupling probability. Finally, a description of how this model can be applied to interacting agents in a financial market is provided.
虽然最近的许多研究都集中在理解网络的孤立级联上,但对于呈现相反影响的重复级联的网络上的动态过程关注较少。金融市场的动态行为就是一个例子,即使在短时间尺度上也会出现买卖级联。为了对这些现象进行建模,描述并分析了一个具有上下阈值的随机脉冲耦合振荡器网络。给出了系统异步和同步状态的数值验证,以及异步平均场系统不动点状态向量的解析识别。找到了网络耦合概率的有限系统平均场临界值的下限,该下限将异步和同步状态区分开来。对于低维平均场系统,找到了一个关于级联规模的封闭形式方程,该方程是网络耦合概率的函数。最后,提供了该模型如何应用于金融市场中相互作用主体的描述。